New ST-segment elevation myocardial infarction criteria for left bundle branch block based on QRS area

Richard E Gregg1, Eric D Helfenbein, Saeed Babaeizadeh

  • 1Advanced Algorithm Research Center, Philips Healthcare, Andover, MA, USA.

Insights

A new algorithm using QRS area improves ST-segment elevation myocardial infarction (STEMI) detection in left bundle-branch block (LBBB) by enhancing sensitivity. Different algorithms offer trade-offs between sensitivity and specificity for STEMI diagnosis in LBBB patients.

Area of Science:

  • Cardiology
  • Medical Imaging
  • Algorithm Development

Background:

  • Detecting ST-segment elevation myocardial infarction (STEMI) with left bundle-branch block (LBBB) on ECG is challenging due to altered conduction causing ST deviation.
  • Existing algorithms for STEMI detection in LBBB have limitations in balancing sensitivity and specificity.

Purpose of the Study:

  • To introduce a novel algorithm for STEMI detection in the presence of LBBB.
  • To compare the performance of the new algorithm against three established criteria: Sgarbossa, Selvester 10% RS, and Smith 25% S-wave.

Main Methods:

  • The study analyzed ECG data from 143 acute myocardial infarction (MI) patients and 239 controls, with LBBB identified by computer interpretation.
  • A new algorithm utilizing an ST threshold based on QRS area was developed and compared with Sgarbossa, Selvester, and Smith criteria.
  • Performance was evaluated using sensitivity, specificity, and positive likelihood ratio (LR+), with variations tested for single and 2-lead requirements.

Main Results:

  • Algorithm performance varied, with the Sgarbossa score (≥3) showing the lowest sensitivity (13.3%) and highest specificity (97.9%).
  • The Selvester 10% rule demonstrated the highest sensitivity (30.1%) but lower specificity (93.2%).
  • The novel Philips QRS area (23.8% sensitivity, 95.8% specificity) and Smith S-wave (20.3% sensitivity, 94.9% specificity) algorithms performed intermediately.

Conclusions:

  • Discordant ST elevation criteria enhance STEMI detection sensitivity in LBBB but can reduce specificity.
  • The Selvester algorithm is preferable for applications prioritizing high sensitivity in STEMI detection.
  • For scenarios demanding low false positive rates, such as pre-hospital activation for urgent PCI, the Philips QRS area or Smith 25% S-wave algorithms may be more suitable.
Abstract

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